On the Equivalence of Nonnegative Matrix Factorization and Spectral Clustering

Current nonnegative matrix factorization (NMF) deals with X = FG type. We provide a systematic analysis and extensions of NMF to the symmetric W = HH , and the weighted W = HSH . We show that (1) W = HH is equivalent to Kernel K-means clustering and the Laplacian-based spectral clustering. (2) X = FG is equivalent to simultaneous clustering of rows and columns of a bipartite graph. Algorithms are given for computing these symmetric NMFs.

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